Add coffee map example (geocompx#145)

* Add coffee map example

* Update coffee data example

* Add variable name

* Update vignette code


Former-commit-id: be27f22
Former-commit-id: 6d13478

extdata/coffee-data-messy.csv

@@ -0,0 +1,65 @@
+Monthly export statistics - November 2017,,,,,,
+In thousand 60kg bags,,,,,,
+,November 2016,November 2017,% change,October - November,,
+,,,,2016/17,2017/18,% change
+TOTAL,9 930,9 019,-9.2%,19 862,17 615,-11.3%
+Arabicas,6 410,6 060,-5.5%,12 736,11 836,-7.1%
+Colombian Milds,1 437,1 272,-11.5%,2 752,2 473,-10.1%
+Other Milds,1 590,1 734,9.1%,3 158,3 243,2.7%
+Brazilian Naturals,3 383,3 054,-9.7%,6 826,6 120,-10.3%
+Robustas,3 520,2 959,-15.9%,7 127,5 779,-18.9%
+Angola,0,0,,0,0,
+Bolivia,3,4,42.5%,5,8,48.9%
+Brazil,3 277,2 786,-15.0%,6 640,5 663,-14.7%
+Burundi,37,38,3.0%,66,72,8.5%
+Cameroon,8,6,-21.8%,15,18,16.9%
+Central African Republic,0,0,,0,0,
+"Congo, Dem. Rep. of",4,12,240.9%,7,24,267.7%
+Colombia,1 330,1 169,-12.1%,2 560,2 293,-10.5%
+Costa Rica,28,32,14.6%,71,46,-34.8%
+Côte d'Ivoire,114,130,14.4%,165,202,22.1%
+Cuba,0,0,,0,0,
+Dominican Republic,1,0,,2,2,49.8%
+Ecuador,87,62,-28.2%,192,133,-30.8%
+El Salvador,5,8,54.4%,16,23,41.4%
+Ethiopia,215,283,32.1%,424,560,31.9%
+Gabon,0,0,,0,0,
+Ghana,1,1,17.2%,2,2,17.2%
+Guatemala,58,70,20.9%,105,130,23.8%
+Honduras,149,165,11.2%,214,217,1.7%
+India,453,566,25.0%,887,1 014,14.4%
+Indonesia,742,360,-51.5%,1 643,960,-41.6%
+Jamaica,0,1,,1,1,51.9%
+Kenya,60,50,-16.2%,113,98,-13.4%
+Liberia,0,0,,0,0,
+Madagascar,3,5,39.4%,8,9,16.6%
+Malawi,3,1,-60.2%,3,2,-40.5%
+Mexico,151,220,45.6%,340,420,23.5%
+Nepal,0,0,,0,0,
+Nicaragua,42,45,7.1%,97,99,2.1%
+Panama,3,3,13.6%,8,6,-27.4%
+Papua New Guinea,114,74,-35.1%,256,161,-37.2%
+Paraguay,0,0,,0,0,
+Peru,585,625,6.8%,1 175,1 228,4.5%
+Philippines,2,0,,5,0,
+Rwanda,36,42,16.9%,75,82,9.8%
+Sierra Leone,1,3,114.4%,3,6,86.8%
+Tanzania,81,66,-18.1%,150,137,-8.7%
+Thailand,39,16,-59.5%,80,32,-60.0%
+Timor-Leste,14,2,-85.3%,25,4,-83.7%
+Togo,2,3,0.1%,4,5,19.1%
+Uganda,408,443,8.7%,617,825,33.7%
+Venezuela,0,0,,0,0,
+Vietnam,1 844,1 700,-7.8%,3 817,3 075,-19.4%
+Yemen,4,1,-82.8%,10,2,-84.6%
+Zambia,3,0,,4,0,
+Zimbabwe,1,1,-47.8%,2,1,-38.2%
+Others,23,26,12.7%,55,56,1.2%
+Note: Group sub-totals take into account the corresponding share of each type of coffee exported by countries that produce and,,,,,,
+"export both Arabica and Robusta in significant volumes. It should be noted that, where applicable, an Arabica/Robusta ratio of",,,,,,
+50/50 has been used to convert processed coffee into Green Bean Equivalent (GBE),,,,,,
+"A figure of 0 in the table can mean a volume of less than 500 bags, due to rounding. Full data in Excel format are available to paid",,,,,,
+subscribers,,,,,,
+Next update: 31 January 2018,,,,,,
+ International Coffee Organization,,,,,,
+

extdata/coffee-data.csv

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+name_long,y16,y17
+Colombian Milds,1437,1272
+Other Milds,1590,1734
+Brazilian Naturals,3383,3054
+Robustas,3520,2959
+Angola,0,0
+Bolivia,3,4
+Brazil,3277,2786
+Burundi,37,38
+Cameroon,8,6
+Central African Republic,0,0
+"Congo, Dem. Rep. of",4,12
+Colombia,1330,1169
+Costa Rica,28,32
+Côte d'Ivoire,114,130
+Cuba,0,0
+Dominican Republic,1,0
+Ecuador,87,62
+El Salvador,5,8
+Ethiopia,215,283
+Gabon,0,0
+Ghana,1,1
+Guatemala,58,70
+Honduras,149,165
+India,453,566
+Indonesia,742,360
+Jamaica,0,1
+Kenya,60,50
+Liberia,0,0
+Madagascar,3,5
+Malawi,3,1
+Mexico,151,220
+Nepal,0,0
+Nicaragua,42,45
+Panama,3,3
+Papua New Guinea,114,74
+Paraguay,0,0
+Peru,585,625
+Philippines,2,0
+Rwanda,36,42
+Sierra Leone,1,3
+Tanzania,81,66
+Thailand,39,16
+Timor-Leste,14,2
+Togo,2,3
+Uganda,408,443
+Venezuela,0,0
+Vietnam,1844,1700
+Yemen,4,1
+Zambia,3,0
+Zimbabwe,1,1
+Others,23,26
+Note: Group sub-totals take into account the corresponding share of each type of coffee exported by countries that produce and,NA,NA
+"export both Arabica and Robusta in significant volumes. It should be noted that, where applicable, an Arabica/Robusta ratio of",NA,NA
+50/50 has been used to convert processed coffee into Green Bean Equivalent (GBE),NA,NA
+"A figure of 0 in the table can mean a volume of less than 500 bags, due to rounding. Full data in Excel format are available to paid",NA,NA
+subscribers,NA,NA
+Next update: 31 January 2018,NA,NA
+ International Coffee Organization,NA,NA

vignettes/coffee-map.R

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+library(tidyverse)
+library(spData)
+library(sf)
+# found by searching for "global coffee data"
+# u = "http://www.ico.org/prices/m1-exports.pdf"
+# download.file(u, "data.pdf")
+# install.packages("pdftables") # also requires an api key
+# pdftables::convert_pdf(input_file = "data.pdf", output_file = "extdata/coffee-data-messy.csv")
+d = read_csv("extdata/coffee-data-messy.csv")
+coffee_data = slice(d, -c(1:5)) %>% 
+  select(name_long = 1, y16 = 2, y17 = 3) %>% 
+  mutate_at(2:3, str_replace, " ", "") %>% 
+  mutate_at(2:3, as.integer)
+write_csv(coffee_data, "extdata/coffee-data.csv")
+world_coffee = left_join(world, coffee_data)
+plot(world_coffee[c("y16", "y17")])
+# library(tmap)
+# qtm(world_coffee, "y17", fill.title = "Thousand 60kg bags")
+# tmap_mode("view") # for an interactive version